What you would learn in Learn Automated Machine Learning : Build Real World Projects course?
Automated Machine Learning provides methods and procedures to allow Machine Learning to be available for non-Machine Learning experts, to enhance the effectiveness and effectiveness of Machine Learning, and to accelerate research into Machine Learning.
Machine learning (ML) has had several successes in recent times, and numerous disciplines are based on it. However, this achievement largely depends on the humans who are experts in machine learning. Complete some of the tasks listed below:
Clean and preprocess the data.
Choose and design the most suitable features.
Choose a suitable model family.
Optimize the model's hyperparameters.
The topology is the design for neural networks (if Deep Learning is used).
Models of machine learning postprocessing.
Analyze the results you have obtained.
Since the difficulty of these tasks is usually beyond the capabilities of non-ML experts, the rapid expansion of machine learning apps has resulted in a demand for off-the-shelf methods that are easy to use and without expertise. We refer to the research area aimed at the gradual automated machine learning AutoML.
It is possible to think of machine learning as an artificial intelligence subset. Techniques because it requires the machine to be able to acquire knowledge faster and more effectively.
In the same way that AI technology is focused on imitating human intelligence, computers learn from their experiences, and machine learning is focused on making computers improve their learning speed and efficiency by leveraging the experience.
In a sense, machine learning can be described as an optimization procedure for AI technology and the machine learning engineer in charge of offering better, more efficient education in AI solutions.
Machine learning aims to create AI solutions faster and more intelligently to provide superior results in whatever mission they've been assigned to accomplish.
Because AI technology can profoundly affect our society and contemporary business practices, it revolutionizes daily tasks from logistics planning to production and operations. Experts in machine learning are in high demand.
- Learn how to do Classification and Regression modeling
- Install Machine Learning algorithms
- Master Machine Learning and use it on the job
- Write clean, maintained, and efficient code that is maintainable, clean, and efficient.
- Make use of Seaborn to create stunning statistical charts using Python.
- Learn how to make use of Scikit-learn to implement powerful machine learning algorithms.
- Set-up is quick and easy with Anaconda's data science stack environment. Anaconda Data Science stack.
- Find out the best practices to follow regarding Data Science Workflow
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